Merging ontology by semantic enrichment and combining similarity measures

  • Authors:

  • Messaouda Fareh;Omar Boussaid;Rachid Chalal;Melyara Mezzi;Khadija Nadji

  • Affiliations:

  • LRDSI Laboratory, Blida University, Soumaa, Algeria;ERIC Laboratory, Lyon 2 University, Campus Porte des Alpes, France;LMCS Laboratory, ESI, Oued-Smar Algier, Algeria;LRDSI Laboratory, Blida University, Soumaa, Algeria;LRDSI Laboratory, Blida University, Soumaa, Algeria

  • Venue:
  • International Journal of Metadata, Semantics and Ontologies
  • Year:
  • 2013

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Abstract

In this paper, we present a new approach to merge OWL ontologies by semantic enrichment of initial ontologies. This work is situated in the general context of stored information heterogeneity in a decisional system such as data, metadata and knowledge, for combination and reconciliation these forms of information by mediation. To add a semantic dimension to the merger, our approach based on semantic enrichment of initial ontologies, this is achieved by enriching initial ontologies by a set of metadata that annotate their concepts with synonyms and homonyms for each concept, via the use of WordNet, or semantic enrichment of an expert, then it generates a thesaurus for each local ontology to build the global thesaurus. Our method focuses on computing semantic similarity between concepts of ontologies, and based on a weighted combination of computing similarity methods, we use syntactic, lexical, structural and semantic techniques, for generating the correspondence matrix; from this latter we generate the merged ontology.